Time-frequency distribution of evoked otoacoustic emissions

Matching Pursuit with Asymmetric Functions for Signal Decomposition and Parameterization

The method of adaptive approximations by Matching Pursuit makes it possible to decompose signals into basic components (called atoms). The approach relies on fitting, in an iterative way, functions from a large predefined set (called dictionary) to an analyzed signal. Usually, symmetric functions coming from the Gabor family (sine modulated Gaussian) are used. However Gabor functions may not be optimal in describing waveforms present in physiological and medical signals. Many biomedical signals contain asymmetric components, usually with a steep rise and slower decay. For the decomposition of this kind of signal we introduce a dictionary of functions of various degrees of asymmetry – from symmetric Gabor atoms to highly asymmetric waveforms. The application of this enriched dictionary to Otoacoustic Emissions and Steady-State Visually Evoked Potentials demonstrated the advantages of the proposed method. The approach provides more sparse representation, allows for correct determination of the latencies of the components and removes the "energy leakage" effect generated by symmetric waveforms that do not sufficiently match the structures of the analyzed signal. Additionally, we introduced a time-frequency-amplitude distribution that is more adequate for representation of asymmetric atoms than the conventional time-frequency-energy distribution.

Use of the matching pursuit algorithm with a dictionary of asymmetric waveforms in the analysis of transient evoked otoacoustic emissions

Transiently evoked otoacoustic emissions (TEOAEs) are normally modeled as the sum of asymmetric waveforms. However, some previous studies of TEOAEs used time-frequency (TF) methods to decompose the signals into symmetric waveforms. This approach was justified mainly as a means to reduce the complexity of the calculations. The present study extended the dictionary of numeric functions to incorporate asymmetric waveforms into the analysis. The necessary calculations were carried out using an adaptive approximation algorithm based on the matching pursuit (MP) numerical technique. The classic MP dictionary uses Gabor functions and consists of waveforms described by five parameters, namely, frequency, latency, time span, amplitude, and phase. In the present investigation, a sixth parameter, the degree of asymmetry, was added in order to enhance the flexibility of this approach. The effects of expanding the available functions were evaluated by means of both simulations using synthetic signals and authentic TEOAEs. The resulting analyses showed that the contributions of asymmetric components in the OAE signal are appreciable. In short, the expanded analysis method brought about important improvements in identifying TEOAE components including the correct detection of components with long decays, which are often related to spontaneous OAE activity, the elimination of a "dark energy" effect in TF distributions, and more reliable estimates of latency-frequency relationships. The latter feature is especially important for correct estimation of latency-frequency data, which is a crucial factor in investigations of OAE-generation mechanisms.

Otoacoustic emissions evoked by 0.5 kHz tone bursts

The aim of this research is to extend previous studies of the time-frequency features of otoacoustic emissions (OAEs) using information about the properties of the signals at low frequencies. Responses to 0.5 kHz tone bursts were compared to OAEs that were evoked by click stimuli and by 1, 2, and 4 kHz tone burst stimuli. The OAEs were measured using 20 and 30 ms intervals between stimuli. The analysis revealed no differences in the time-frequency properties of 1, 2, and 4 kHz bursts measured using these two different acquisition windows. However, at 0.5 kHz the latency of the response was affected significantly if a shorter time window was used. This was caused by the fact that the response reached a maximum after an average time of 15.4 ms, and lasted a few milliseconds longer. Therefore, for this particular stimulus, the use of a 30 ms time window seems more appropriate. In addition, as an example of the possible application of low-frequency OAEs, signals were measured in patients suffering from partial deafness, characterized by steep audiograms with normal thresholds up to 0.5 kHz and almost total deafness above this frequency. Although no response to clicks was observed in these subjects, the use of 0.5 kHz tone bursts did produce OAEs.

Time-frequency analyses of transient-evoked stimulus-frequency and distortion-product otoacoustic emissions: testing cochlear model predictions

Time-frequency representations (TFRs) of otoacoustic emissions (OAEs) provide information simultaneously in time and frequency that may be obscured in waveform or spectral analyses. TFRs were applied to transient-evoked stimulus-frequency (SF) and distortion-product (DP) OAEs to test cochlear model predictions. SFOAEs and DPOAEs were elicited in 18 normal-hearing subjects using gated tones and tone pips. Synchronous spontaneous (SS) OAEs were measured to assess their contributions to SFOAEs and DPOAEs. A common form of TFR of measured OAEs was a collection of frequency-specific components often aligned with SSOAE sites, with each component characterized by one or more brief segments or a single long-duration segment. The spectral envelope of evoked OAEs differed from that of the evoking stimulus. Strong emission regions or cochlear "hot spots" were detected, and sometimes accounted for OAE energy observed outside the stimulus bandwidth. Contributions of hot spots and multiple internal reflections to the OAE, and differences between measured and predicted OAE spectra, increased as stimulus level decreased, consistent with level-dependent changes in the estimated cochlear reflectance. Suppression and frequency-pulling effects between components were observed. A recursive formulation was described for the linear coherent reflection emission theory [Zweig and Shera, J. Acoust. Soc. Am. 98, 2018-2047 (1995)] that is well suited for time-domain calculations.

Time-frequency analyses of TEOAE recordings from normals and SNHL patients

This study evaluated the characteristics of transient evoked otoacoustic emission (TEOAE) time-frequency (TF) representations from normal and hearing-impaired ears. Linear and non-linear TEOAE recordings from normally-hearing subjects (40) and non-linear recordings from patients with sensorineural hearing loss (SNHL) (40) were analysed using the short-time-Fourier-transform spectrogram, the Gabor spectrogram, and the adaptive spectrogram. The TF representations of the TEOAE recordings indicated a considerable dispersion of energy across frequencies and TEOAE time segments >4.0 ms. The linear and non-linear recordings from the normal subjects showed common frequency peaks. The TF representations from the patients with SNHL indicated that the significantly reduced energy in the mid-to-high TEOAE frequencies did not correlate closely with the threshold elevation. As in the recordings from the normal subjects, a high percentage of the TEOAE cumulative energy was found within a short TEOAE segment (4-14 ms).